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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/17885?offset=980</link>
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	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/11368/metagenomics-role-in-antibiotic-resistance</guid>
	<pubDate>Mon, 02 Jun 2014 08:04:40 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/11368/metagenomics-role-in-antibiotic-resistance</link>
	<title><![CDATA[Metagenomics role in antibiotic resistance]]></title>
	<description><![CDATA[<p>Related latest article:</p>
<p><a href="http://www.nature.com/nature/journal/v509/n7502/pdf/nature13377.pdf">http://www.nature.com/nature/journal/v509/n7502/pdf/nature13377.pdf</a></p><p>Address of the bookmark: <a href="https://www.landesbioscience.com/journals/virulence/2013VIRULENCE0033R2.pdf" rel="nofollow">https://www.landesbioscience.com/journals/virulence/2013VIRULENCE0033R2.pdf</a></p>]]></description>
	<dc:creator>Rahul Agarwal</dc:creator>
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/13226/you-and-your-friend-have-similar-dna</guid>
	<pubDate>Sun, 27 Jul 2014 20:44:05 -0500</pubDate>
	<link>https://bioinformaticsonline.com/news/view/13226/you-and-your-friend-have-similar-dna</link>
	<title><![CDATA[You and your friend have similar DNA !!!]]></title>
	<description><![CDATA[<p>New research out of Massachusetts claims that people often choose friends that are similar to them in genetics and they are more accurate than you might suppose. A study published on PNAS&nbsp;http://www.pnas.org/content/111/Supplement_3/10796.full found that people are apt to pick friends who are genetically similar to themselves - so much so that friends tend to be as alike at the genetic level as a person's fourth cousin.</p><div style="text-align: center;"><img src="http://i.kinja-img.com/gawker-media/image/upload/s--CwLwHa43--/18fbmlokxcmqcjpg.jpg" alt="image" width="300" height="271" style="border: 0px; border: 0px;"></div><p>Scientists with a long-running Framingham Heart Study looked at 1,932 people (examination of about 1.5 million markers of genetic variations), comparing unrelated friends to unrelated strangers. They found that friends shared about 1% of their genes &mdash; a percentage much higher than those shared with strangers.This new findings made it clear that people have more DNA in common with those who are selected as friends than with strangers in the same population.&nbsp;</p><p>The genes that lined up the most were olfactory genes, which deal with smell. The ones that lined up the least were immune system genes. The researchers weren't sure why that happened :/. Olfactory genes might be a straightforward explanation: People who like the same smells tend to be drawn to similar environments, where they meet others with the same tendencies.</p><p>Reference:</p><p>http://www.pnas.org/content/111/Supplement_3/10796.full</p><p>Image : http://i.kinja-img.com</p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34396/pore-an-r-package-for-the-visualization-and-analysis-of-nanopore-sequencing-data</guid>
	<pubDate>Thu, 23 Nov 2017 09:55:57 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34396/pore-an-r-package-for-the-visualization-and-analysis-of-nanopore-sequencing-data</link>
	<title><![CDATA[poRe: an R package for the visualization and analysis of nanopore sequencing data]]></title>
	<description><![CDATA[<p><strong>Motivation:</strong>&nbsp;The Oxford Nanopore MinION device represents a unique sequencing technology. As a mobile sequencing device powered by the USB port of a laptop, the MinION has huge potential applications. To enable these applications, the bioinformatics community will need to design and build a suite of tools specifically for MinION data.</p>
<p><strong>Results:</strong>&nbsp;Here we present poRe, a package for R that enables users to manipulate, organize, summarize and visualize MinION nanopore sequencing data. As a package for R, poRe has been tested on Windows, Linux and MacOSX. Crucially, the Windows version allows users to analyse MinION data on the Windows laptop attached to the device.</p>
<p><strong>Availability and implementation:</strong>&nbsp;poRe is released as a package for R at&nbsp;<a href="http://sourceforge.net/projects/rpore/" target="">http://sourceforge.net/projects/rpore/</a>&nbsp;. A tutorial and further information are available at&nbsp;<a href="https://sourceforge.net/p/rpore/wiki/Home/" target="">https://sourceforge.net/p/rpore/wiki/Home/</a></p>
<p><strong>Contact:</strong><a href="mailto:mick.watson@roslin.ed.ac.uk" target="">mick.watson@roslin.ed.ac.uk</a></p><p>Address of the bookmark: <a href="https://academic.oup.com/bioinformatics/article/31/1/114/2365693" rel="nofollow">https://academic.oup.com/bioinformatics/article/31/1/114/2365693</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/13338/protein-function-annotation-and-machine-learning-upmc-paris-france</guid>
  <pubDate>Sat, 02 Aug 2014 01:22:52 -0500</pubDate>
  <link></link>
  <title><![CDATA[Protein function annotation and machine learning - UPMC - Paris, France]]></title>
  <description><![CDATA[
<p>Protein function annotation and machine learning - UPMC - Paris, France</p>

<p>Job Description: We are interested in finding an excellent postdoc with interests in protein functional annotation, machine learning and computer grids. The position is open for 3.5 years at the Université Pierre et Marie Curie, in the heart of paris.</p>

<p>Research topic: Protein function annotation, multiple probabilistic models, domain architecture, machine learning, combinatorial optimization, computer grid.</p>

<p>Title: A novel integrative platform for large scale protein annotation that exploits a multitude of diversified probabilistic models in several protein signature databases.</p>

<p>We propose a novel integrated approach for large scale protein annotation that will exploit an unprecedented amount of genomic data as well as sophisticated machine learning techniques and combinatorial optimization approaches taking advantages of High Performance Computing (HPC) environments. The idea is to uncover as much as possible the evolutionary processes of protein sequences that took place throughout the whole tree of life and that affected the evolution of a protein family. We have already demonstrated in a previous work that the problem of functional annotation is inherent to the ability of uncovering such paths. Now, we shall extend this approach to large scale genome annotation by considering 11 different protein databases, constituted by about 10^9 protein sequences, and by producing a large pool of diversified probabilistic models coding for about 10^7 evolutionary protein pathways. Such models will be used to search for specific domains in genomes to be annotated. Our previous methodology needs to be fundamentally improved to deal with this large amount of biological data. In this project, we shall work on the algorithms to reduce the space of models and the search complexity, and we shall implement some important algorithmic changes towards the realization of a powerful integrated annotation tool.</p>

<p>Where: This project is run on the Laboratoire de Biologie Computationnelle et Quantitative UMR7238 CNRS-UPMC – Analytical Genomics team, headed by A.Carbone. It is co-advised with Pierre-Henri Wuillemin, Laboratoire d’Informatique de Paris 6 – Equipe DECISION.</p>

<p>Start date: September 1st, 2014<br />Contact Person: Alessandra Carbone<br />Contact: alessandra.carbone@lip6.fr</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34867/magic-blast-a-tool-for-mapping-large-next-generation-rna-or-dna-sequencing-runs-against-a-whole-genome-or-transcriptome</guid>
	<pubDate>Tue, 26 Dec 2017 22:23:39 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34867/magic-blast-a-tool-for-mapping-large-next-generation-rna-or-dna-sequencing-runs-against-a-whole-genome-or-transcriptome</link>
	<title><![CDATA[Magic-BLAST: a tool for mapping large next-generation RNA or DNA sequencing runs against a whole genome or transcriptome.]]></title>
	<description><![CDATA[<p>Magic-BLAST is a tool for mapping large next-generation RNA or DNA sequencing runs against a whole genome or transcriptome. Each alignment optimizes a composite score, taking into account simultaneously the two reads of a pair, and in case of RNA-seq, locating the candidate introns and adding up the score of all exons. This is very different from other versions of BLAST, where each exon is scored as a separate hit and read-pairing is ignored.</p>
<p>Magic-BLAST incorporates within the NCBI BLAST code framework ideas developed in the NCBI Magic pipeline, in particular hit extensions by local walk and jump&nbsp;<a href="http://www.ncbi.nlm.nih.gov/pubmed/26109056">(http://www.ncbi.nlm.nih.gov/pubmed/26109056)</a>, and recursive clipping of mismatches near the edges of the reads, which avoids accumulating artefactual mismatches near splice sites and is needed to distinguish short indels from substitutions near the edges.</p><p>Address of the bookmark: <a href="https://ncbi.github.io/magicblast/" rel="nofollow">https://ncbi.github.io/magicblast/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/13842/swabs-to-genomes-a-comprehensive-workflow</guid>
	<pubDate>Sun, 10 Aug 2014 03:01:21 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/13842/swabs-to-genomes-a-comprehensive-workflow</link>
	<title><![CDATA[Swabs to Genomes: A Comprehensive Workflow]]></title>
	<description><![CDATA[<p>The sequencing, assembly, and basic analysis of microbial genomes, once a painstaking and expensive undertaking, has become almost trivial for research labs with access to standard molecular biology and computational tools. However, there are a wide variety of options available for DNA library preparation and sequencing, and inexperience with bioinformatics can pose a significant barrier to entry for many who may be interested in microbial genomics. The objective of the present study was to design, test, troubleshoot, and publish a simple, comprehensive workflow from the collection of an environmental sample (a swab) to a published microbial genome; empowering even a lab or classroom with limited resources and bioinformatics experience to perform it.</p><p>Address of the bookmark: <a href="https://peerj.com/preprints/453.pdf" rel="nofollow">https://peerj.com/preprints/453.pdf</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36456/alpaca-a-hybrid-strategy-for-assembly-of-genomic-dna-shotgun-sequencing-reads</guid>
	<pubDate>Mon, 30 Apr 2018 04:38:40 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36456/alpaca-a-hybrid-strategy-for-assembly-of-genomic-dna-shotgun-sequencing-reads</link>
	<title><![CDATA[ALPACA: A hybrid strategy for assembly of genomic DNA shotgun sequencing reads.]]></title>
	<description><![CDATA[<p><span>ALPACA requires Celera Assembler 8.3 or later. It is recommended to build Celera Assembler from source. (Why? The pre-built binaries CA_8.3rc1 and CA8.3rc2 will work for any large data set.&nbsp;</span></p>
<p><span>Detail paper at&nbsp;https://bmcgenomics.biomedcentral.com/articles/10.1186/s12864-017-3927-8</span></p><p>Address of the bookmark: <a href="https://github.com/VicugnaPacos/ALPACA" rel="nofollow">https://github.com/VicugnaPacos/ALPACA</a></p>]]></description>
	<dc:creator>Seema Singh</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/14050/assistant-professor-in-bioinformatics-at-indian-institute-of-technology-delhi</guid>
  <pubDate>Fri, 15 Aug 2014 06:16:06 -0500</pubDate>
  <link></link>
  <title><![CDATA[Assistant Professor 	in Bioinformatics at Indian Institute of Technology Delhi]]></title>
  <description><![CDATA[
<p>Indian Institute of Technology Delhi Hauz Khas ,New Delhi – 110016</p>

<p>ROLLING ADVERTISEMENT NO. 01/2014(E-1)<br />ADVERTISEMENT FOR THE POSITIONS OF ASSISTANT PROFESSOR CANDIDATES CAN APPLY ANY TIME DURING THE YEAR.</p>

<p>IIT Delhi invites applications from qualified Indian Nationals, Persons of Indian Origin (PIOs) and Overseas Citizens of India (OCIs) for the following positions in the various Departments/Centres/Schools (in the fields<br />mentioned alongwith them):<br />Post Pay Band Assistant Professor and Assistant Professor (on Contract) Rs.15600-39100 (PB-3) (Minimum pay of Rs.30000/-)+ AGP Rs.8000/-</p>

<p>The following norms will be followed for fixing the basic pay + AGP for Assistant Professors appointed on<br />contract with Ph.D but experience of 3 years or less:-<br />Type Qualification &amp; Experience on the date of joining<br />Assistant Professor (Contract) PB3 (Rs. 15,600-39,100).</p>

<p>MINIMUM QUALIFICATIONS AND EXPERIENCE:<br />Ph.D. with First class at the preceding degree or equivalent in the appropriate branch with very good academic record throughout. A minimum of three years industrial/research/teaching experience, excluding however, the experience gained while Pursuing Ph. D. The candidates should preferably be below<br />35 years of age for male and 38 years for female ( to be relaxed by 5 years in case of persons with physical disability, SC/ST and 3 years in case of OBC-NCL).</p>

<p>Qualified persons include:<br />(a) Indian Nationals,<br />(b) Foreign Nationals who are “Persons of Indian Origin” (PIO) or Overseas<br />Citizens of India (OCI), in whose case, if selected, permission will be sought from Govt. of India<br />before he/she can join IIT Delhi, or<br />(c) Other Foreign Nationals, in whose case, if selected, appointment will be on a contract basis for up to 5 (five) years subject to permission from the Govt. of India before he/she can join IIT Delhi.<br />(d) Institute specifically encourages applicants from SC/ST/OBC category as well as persons<br />with disability to apply for these positions. </p>

<p>AMAR NATH &amp; SHASHI KHOSLA SCHOOL OF INFORMATION TECHNOLOGY:<br />Computational Neuroscience, Medical Applications of Information Technologies, Computational &amp; Systems Biology, Machine to Machine (M2M) Technologies, Embedded Systems &amp; Sensors, Computer Security.<br />KUSUMA SCHOOL OF BIOLOGICAL SCIENCES:<br />In-silico Biology Applications, Systems Biology, Infection Biology, Neurodegeneration. </p>

<p>More at http://www.iitd.ac.in/sites/default/files/jobs/faculty/spl-areas-rolling-advt.pdf</p>

<p>http://www.iitd.ac.in/content/faculty-positions</p>
]]></description>
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<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36621/hapcut2-robust-and-accurate-haplotype-assembly-for-diverse-sequencing-technologies</guid>
	<pubDate>Tue, 15 May 2018 07:35:26 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36621/hapcut2-robust-and-accurate-haplotype-assembly-for-diverse-sequencing-technologies</link>
	<title><![CDATA[HapCUT2: robust and accurate haplotype assembly for diverse sequencing technologies]]></title>
	<description><![CDATA[HapCUT2 is a maximum-likelihood-based tool for assembling haplotypes from DNA sequence reads, designed to "just work" with excellent speed and accuracy. We found that previously described haplotype assembly methods are specialized for specific read technologies or protocols, with slow or inaccurate performance on others. With this in mind, HapCUT2 is designed for speed and accuracy across diverse sequencing technologies, including but not limited to:

NGS short reads (Illumina HiSeq)
clone-based sequencing (Fosmid or BAC clones)
SMRT reads (PacBio)
Oxford Nanopore reads
10X Genomics Linked-Reads
proximity-ligation (Hi-C) reads
high-coverage sequencing (&gt;40x coverage-per-SNP) using above technologies
combinations of the above technologies (e.g. scaffold long reads with Hi-C reads)
See below for specific examples of command line options and best practices for some of these technologies.

NOTE: At this time HapCUT2 is for diploid organisms only. VCF input should contain diploid variants.

If you use HapCUT2 in your research, please cite:

Edge, P., Bafna, V. &amp; Bansal, V. HapCUT2: robust and accurate haplotype assembly for diverse sequencing technologies. Genome Res. gr.213462.116 (2016). doi:10.1101/gr.213462.116<p>Address of the bookmark: <a href="https://github.com/vibansal/HapCUT2" rel="nofollow">https://github.com/vibansal/HapCUT2</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/14272/lecturersenior-lecturer-level-bc-in-bioinformatics</guid>
  <pubDate>Fri, 22 Aug 2014 12:45:52 -0500</pubDate>
  <link></link>
  <title><![CDATA[Lecturer/Senior Lecturer (Level B/C) in Bioinformatics]]></title>
  <description><![CDATA[
<p>Lecturer/Senior Lecturer (Level B/C) in Synthetic Biology, Research Fellow (Level B) in Synthetic Biology &amp; Lecturer/Senior Lecturer (Level B/C) in Bioinformatics</p>

<p>Apply now Job no: 494553<br />Work type: Continuing full time<br />Vacancy type: External Vacancy, Internal Vacancy<br />Categories: Academic - Teaching and Research</p>

<p>The Faculty of Science is launching a new and innovative branch of biological science at Macquarie University – Synthetic Biology. Synthetic biology combines engineering principles with molecular biological approaches to design and construct biological devices and systems. Recent highlights in this field include the design and synthesis of a functional bacterial genome and a yeast chromosome, and generation of synthetic bacterial cells. The rational synthesis of "designer" organisms yield important insights into how organisms work and has the potential to revolutionise biotechnological applications in areas such as bioenergy and biomanufacturing.</p>

<p>Find more at http://jobs.mq.edu.au/cw/en/job/494553/lecturersenior-lecturer-level-bc-in-synthetic-biology-research-fellow-level-b-in-synthetic-biology-lecturersenior-lecturer-level-bc-in-bioinformatics</p>
]]></description>
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